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Estimating the unseen emergence of COVID-19 in the US
Javan, E. M.; Fox, S. J.; Meyers, L. A.
2020-11-13
infectious diseases
10.1101/2020.04.06.20053561
medRxiv
Show abstract
For each US county, we calculated the probability of an ongoing COVID-19 epidemic that may not yet be apparent. Based on confirmed cases as of April 15, 2020, COVID-19 is likely spreading in 86% of counties containing 97% of US population. Proactive measures before two cases are confirmed are prudent.
Matching journals
●Non-profit
◐University press
○Commercial
The top 7 journals account for 50% of the predicted probability mass.
1
PLOS Computational Biology
●
1863 papers in training set
Top 2%
12.8%
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- Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: results of a Bayesian evidence synthesis model 96%
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- Using Test Positivity and Reported Case Rates to Estimate State-Level COVID-19 Prevalence and Seroprevalence in the United States 95%
2
PLOS ONE
●
5266 papers in training set
Top 16%
11.8%
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- Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction 95%
- Threshold analyses on rates of testing, transmission, and contact for COVID-19 control in a university setting 95%
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4
Epidemics
○
116 papers in training set
Top 0.3%
6.2%
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- Predicting the impact of COVID-19 non-pharmaceutical intervention on short- and medium-term dynamics of enterovirus D68 in the US 95%
- Using an Agent-Based Model to Assess K-12 School Reopenings Under Different COVID-19 Spread Scenarios – United States, School Year 2020/21 94%
- Incident COVID-19 infections before Omicron in the U.S 94%
50% of probability mass above
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.